VLMS Are Blind
Multimodal dataset composed of 8,016 examples, combining visual and textual data. It is designed to train models capable of understanding and generating content that combines vision and language.
8,016 examples, Parquet format, size 83.5 MB, data combining images and text
MIT
Description
The dataset VLMS Are Blind contains over 8,000 examples combining images and text, stored in Parquet format. This multimodal data is adapted to models that deal with both visual and textual information.
What is this dataset for?
- Train multimodal models integrating vision and language (VL-models)
- Develop image recognition systems with text annotations
- Testing the joint understanding of images and text in AI tasks
Can it be enriched or improved?
Yes, it is possible to complete this dataset with additional annotations, in particular by adding semantic metadata or by enriching text descriptions. Specific annotations could improve the accuracy of the models.
🔎 In summary
🧠 Recommended for
- Vision and Language Researchers
- VL-Models Developers
- Multimodal projects
🔧 Compatible tools
- PyTorch
- TensorFlow
- Hugging Face Transformers
- Pandas (for Parquet)
💡 Tip
Use frameworks that support Parquet for effective treatment.
Frequently Asked Questions
What is the exact nature of the data in this dataset?
The dataset contains multimodal examples combining images and text, perfect for vision-language models.
Can I use this dataset for commercial projects?
Yes, the MIT license allows free use, including commercial use.
Do you need special skills to use this dataset?
A basic knowledge of Parquet formats and ML frameworks is recommended for optimal use.
